Impact of Urea-Intercalated-Biochar on N-Release in Soil and Humified Soil Organic Matter
Bibliographic record
Abstract
This research investigated the impact of urea-intercalated-biochar (ICB) on nitrogen release as well as on humified soil organic matter (SOM) distribution in highly weathered soil. Incubation studies were performed with a typical dystrophic red Ultisol and with 10 treatments: soil without amendment (control, CON), soil with three doses of biochar (BC75, BC145, and BC 290), and soil with ICB doses (ICB75, ICB145 and ICB 290). BC and ICB were characterized by 13C Nuclear Magnetic Resonance 13C-NMR CP/MAS spectroscopy and elemental analyses. N-extractable forms were periodically determined by Kjeldahl method and humic substances (HS) distribution was analyzed on the 28th day after incubation begins (DAI). Intercalation of urea in BC increased sample N content from 2.7 to 22 %, whereas that of C decreased from 40 % to 28 %. As a consequence, C: N decreased from 14.9 to 1.3. The 13C NMR spectra of BC and ICB were similar but relative abundance of major organic functional groups differs, for example, ICB presented a greater proportion of C=O groups due to the carbonyl group of urea and a greater proportion of N/O alkyl C, O-alkyl C, and anomeric C groups due to the addition of starch. There was a significant increase in the concentration of extractable N-NH4+ by addition of urea from the onset of incubation down late period and a significant difference (P > 0.05) was obtained between the ICB and BC over time. This could be as a result of the less accessible form of N in the biochar materials due to the pyrolysis process. There was no evidence of extractable N-NO3- ion until 14 DAI, significant difference in N-NH4+ concentrations at 28 DAI between the ICB and control was observed over time and the highest value recorded from ICB treated pots at 145 and 290 kg N ha-1.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".